An energy minimimization and molecular design algorithm based upon the structural parameterization of the energetics has been used to design and predict the binding affinity of mutants of the aspartic protease inhibitor pepstatin A. The simplest design strategy involves mutation and/or chain length modification of the wild type peptide inhibitor. The structural parameterization allows evaluation of the contribution of different amino acids to the Gibbs energy, and therefore the identification of potential targets for mutation in the original peptide. The structure of the wild type complex is used as a template to generate families of conformational structures in which specific residues have been mutated. The most probable conformations of the mutated peptides are identified by systematically rotating around the side chain and backbone torsional angles. In this paper we have tested this approach by chemically synthesizing two different mutants of pepstatin A. In one mutant, the alanine at position five has been replaced by a phenylalanine, and in the second one a glutamate has been added at the carboxy terminus of pepstatin A. The thermodynamics of association of pepstatin A and the two mutants have been measured experimentally and the results compared with the predictions. The difference between experimental and predicted Gibbs energies for pepstatin A and the two mutants is 0.23 q 0.06 kcal/mol. The excellent agreement between experimental and predicted values demonstrates that this approach can be used in the optimization of peptide ligands.